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I applied via Naukri.com and was interviewed in Sep 2024. There was 1 interview round.
The number of cars that can pass in an hour at a 4-way signal depends on various factors such as traffic flow, signal timing, and road capacity.
The capacity of a 4-way signal intersection depends on the traffic flow from each direction
Signal timing and coordination can affect the number of cars that can pass through the intersection
Road capacity and lane configuration also play a role in determining the throughput of t
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor performance on unseen data as the model fails to generalize well.
Techniques to prevent overfitting include cross-validation, regularization, and early stopping.
...
Overfitting occurs when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
Overfitting happens when a model is too complex and captures noise in the training data.
It leads to poor generalization and high accuracy on training data but low accuracy on new data.
Techniques to prevent overfitting include cross-validation, regularization, and...
Forecasting problem - Predict daily sku level sales
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
Bias is the error introduced by approximating a real-world problem, leading to underfitting.
Variance is the error introduced by modeling the noise in the training data, leading to overfitting.
High bias can cause a model to miss relevant relationships between features and target variable.
High variance can cause a model to ...
Parametric models make strong assumptions about the form of the underlying data distribution, while non-parametric models do not.
Parametric models have a fixed number of parameters, while non-parametric models have a flexible number of parameters.
Parametric models are simpler and easier to interpret, while non-parametric models are more flexible and can capture complex patterns in data.
Examples of parametric models inc...
posted on 1 Aug 2023
I was interviewed in Feb 2023.
posted on 29 Feb 2024
I applied via Approached by Company and was interviewed before Mar 2023. There were 3 interview rounds.
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